Several statistical measures exist. One of the most common is Kyle's Lambda, estimated as the coefficient \lambda from regressing price changes P_t on trade size y_t over some time window. : \mathrm{P}_t = \mu + \lambda\mathrm{y}_t For very short periods, this reduces to simply : \lambda = \frac{\Delta \mathrm{Price}_t}{\mathrm{OrderFlow}_t} Order flow is typically measured as the total number of shares traded. Under this measure, a highly liquid stock is one that experiences a small price change for a given level of orders. Kyle's lambda is named from Pete Kyle's famous paper on
market microstructure. Practitioners sometimes model market impact as proportional to the
square root of traded volume, an approach that is supported by research. Alternatively, some evidence suggests a
logarithmic relationship. == Unique challenges for microcap traders ==